Abstract
SummaryBackgroundMultiple blood transcriptional signatures have been proposed for identification of active and incipient tuberculosis. We aimed to compare the performance of systematically identified candidate signatures for incipient tuberculosis and to benchmark these against WHO targets.MethodsWe did a systematic review and individual participant data meta-analysis. We searched Medline and Embase for candidate whole blood mRNA signatures discovered with the primary objective of diagnosis of active or incipient tuberculosis, compared with controls who were healthy or had latent tuberculosis infection. We tested the performance of eligible signatures in whole blood transcriptomic datasets, in which sampling before tuberculosis diagnosis was done and time to disease was available. Culture-confirmed and clinically or radiologically diagnosed pulmonary or extrapulmonary tuberculosis cases were included. Non-progressor (individuals who remained tuberculosis-free during follow-up) samples with less than 6 months of follow-up from the date of sample collection were excluded, as were participants with prevalent tuberculosis and those who received preventive therapy. Scores were calculated for candidate signatures for each participant in the pooled dataset. Receiver operating characteristic curves, sensitivities, and specificities were examined using prespecified intervals to tuberculosis (<3 months, <6 months, <1 year, and <2 years) from sample collection. This study is registered with PROSPERO, number CRD42019135618.ResultsWe tested 17 candidate mRNA signatures in a pooled dataset from four eligible studies comprising 1126 samples. This dataset included 183 samples from 127 incipient tuberculosis cases in South Africa, Ethiopia, The Gambia, and the UK. Eight signatures (comprising 1–25 transcripts) that predominantly reflect interferon and tumour necrosis factor-inducible gene expression, had equivalent diagnostic accuracy for incipient tuberculosis over a 2-year period with areas under the receiver operating characteristic curves ranging from 0·70 (95% CI 0·64–0·76) to 0·77 (0·71–0·82). The sensitivity of all eight signatures declined with increasing disease-free time interval. Using a threshold derived from two SDs above the mean of uninfected controls to prioritise specificity and positive-predictive value, the eight signatures achieved sensitivities of 24·7–39·9% over 24 months and of 47·1–81·0% over 3 months, with corresponding specificities of more than 90%. Based on pre-test probability of 2%, the eight signatures achieved positive-predictive values ranging from 6·8–9·4% over 24 months and 11·2–14·4% over 3 months. When using biomarker thresholds maximising sensitivity and specificity with equal weighting to both, no signature met the minimum WHO target product profile parameters for incipient tuberculosis biomarkers over a 2-year period.InterpretationBlood transcriptional biomarkers reflect short-term risk of tuberculosis and only exceed WHO benchmarks if applied to 3–6-month intervals. Serial testing among carefully selected target groups might be required for optimal implementation of these biomarkers.FundingWellcome Trust and National Institute for Health Research.
Highlights
Eight signatures that predominantly reflect interferon and tumour necrosis factor-inducible gene expression, had equivalent diagnostic accuracy for incipient tuberculosis over a 2-year period with areas under the receiver operating characteristic curves ranging from 0·70 to 0·77 (0·71–0·82)
Identification of people at high risk of developing tuberculosis enables the delivery of preventive treatment for a disease that accounts for more deaths than any other infectious disease worldwide, with an estimated 10 million incident cases and 1·6 million deaths in 2017.1 This approach represents a fundamental component of the WHO End TB strategy, aiming for a 95% reduction in tuberculosis mortality and 90% reduction in tuber culosis incidence by 2035.2 these efforts are undermined by the poor positive predictive value of available prognostic tests for development of tuberculosis, which focus on the identification of a T-cell-mediated response to mycobacterial antigen stimulation, as a surrogate for latent tuberculosis infection.[3,4]
We show that a single transcript (BATF2) and seven other multi-transcript signatures, regulated by interferon signalling, perform with equivalent diagnostic accuracy for incipient tuberculosis
Summary
Identification of people at high risk of developing tuberculosis enables the delivery of preventive treatment for a disease that accounts for more deaths than any other infectious disease worldwide, with an estimated 10 million incident cases and 1·6 million deaths in 2017.1 This approach represents a fundamental component of the WHO End TB strategy, aiming for a 95% reduction in tuberculosis mortality and 90% reduction in tuber culosis incidence by 2035.2 these efforts are undermined by the poor positive predictive value of available prognostic tests for development of tuberculosis, which focus on the identification of a T-cell-mediated response to mycobacterial antigen stimulation, as a surrogate for latent tuberculosis infection.[3,4] These tests include the tuberculin skin test and interferon-γ release assays (IGRAs), which have positive predictive values of 1–6% for incident tuberculosis over a 2-year period.[4,5,6,7] The poor predictive value of available diagnostics precludes precise delivery of preventive therapy, www.thelancet.com/respiratory Vol 8 April 2020Research in contextEvidence before this study We did a systematic review using comprehensive terms for “tuberculosis”, “transcriptome”, “signature” and “blood”, without language or date restrictions, on April 15, 2019. Multiple studies have identified perturbation in the transcriptome that predates clinical diagnosis of tuberculosis and have discovered and assessed performance of one or more signatures for diagnosis of incipient tuberculosis within individual datasets. A head-to-head evaluation of candidate signatures was done, but omitted key signatures, and compared diagnostic accuracy for incipient tuberculosis in only a single dataset over a 0–6-month period. No previous studies have directly compared the diagnostic accuracy of all candidate signatures in a patient-level pooled dataset. It was unknown which signature performs best for diagnosis of incipient tuberculosis, or whether any meets WHO target product profile benchmarks (aiming for sensitivity ≥75% and specificity ≥75% over 2 years)
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